JUL 28, 2021 7:00 AM PDT

Population bottlenecks strongly affect the evolutionary dynamics of antibiotic persistence

Sponsored by: Inscripta
C.E. Credits: P.A.C.E. CE Florida CE
Speaker

Abstract
Date:  July 28, 2021
Time: 7:00am (PDT),  10:00am (EDT)
 
Bacterial persistence is a potential cause of antibiotic therapy failure. Antibiotic-tolerant persisters originate from phenotypic differentiation within a susceptible population, occurring with a frequency that can be altered by mutations. Recent studies have proven that persistence is a highly evolvable trait and, consequently, an important evolutionary strategy of bacterial populations to adapt to high-dose antibiotic therapy. Yet, the factors that govern the evolutionary dynamics of persistence are currently poorly understood. Theoretical studies predict far-reaching effects of bottlenecking on the evolutionary adaptation of bacterial populations, but these effects have never been investigated in the context of persistence. Bottlenecking events are frequently encountered by infecting pathogens during host-to-host transmission and antibiotic treatment. In this study, we used a combination of experimental evolution and barcoded knockout libraries to examine how population bottlenecking affects the evolutionary dynamics of persistence. In accordance with existing hypotheses, small bottlenecks were found to restrict the adaptive potential of populations and result in more heterogeneous evolutionary outcomes. Evolutionary trajectories followed in small-bottlenecking regimes additionally suggest that the fitness landscape associated with persistence has a rugged topography, with distinct trajectories towards increased persistence that are accessible to evolving populations. Furthermore, sequencing data of evolved populations and knockout libraries after selection reveal various genes that are potentially involved in persistence, including previously known as well as novel targets. Together, our results do not only provide experimental evidence for evolutionary theories, but also contribute to a better understanding of the environmental and genetic factors that guide bacterial adaptation to antibiotic treatment.
 
Learning Objectives:
  • Demonstrate how to apply adaptive laboratory evolution (ALE) to study population dynamics of antibiotic persistence
  • Identify environmental and genetic factors that that guide bacterial adaptation to antibiotic treatment
  • Review why narrow bottlenecking events restrict the adaptive potential of populations
  • Explain how the divergent evolutionary trajectories point to a rugged fitness landscape
 
 
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